Estimating and compensating for noise in a multi-antenna wireless system

ABSTRACT

A method for estimating and compensating for noise on antennas of a multi-antenna wireless system. The method includes receiving multiple signals via multiple receive antennas of a receiver, where each of the signals is received via a respective antenna. The method further includes estimating noise power imbalance corresponding to the receive antennas based on the multiple signals.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.12/435,166, filed on May 4, 2009, which claims the benefit of U.S.Provisional Patent App. No. 61/055,029 entitled “Method and Noise PowerImbalance Estimation in WLAN Systems,” filed May 21, 2008, thedisclosure of each is hereby expressly incorporated herein by referencein its entirety.

FIELD OF TECHNOLOGY

The present disclosure relates generally to multi-antenna wirelesssystems and, more particularly, to estimating and compensating for noiseon antennas of a multi-antenna wireless system.

BACKGROUND

An ever-increasing number of relatively inexpensive, low power wirelessdata communication services, networks and devices have been madeavailable over the past number of years, promising near wire speedtransmission and reliability. Various wireless technology is describedin detail in the 802 IEEE Standards, including for example, the IEEEStandard 802.11a (1999) and its updates and amendments, the IEEEStandard 802.11g (2003), and the IEEE Standard 802.11n now in theprocess of being adopted, all of which are collectively incorporatedherein fully by reference. These standards have been or are in theprocess of being commercialized with the promise of 54 Mbps or higherdata rate, making the wireless technology a strong competitor totraditional wired Ethernet and the more common “802.11b” or “WiFi” 11Mbps mobile wireless transmission standard.

Generally speaking, transmission systems compliant with the IEEE 802.11aand 802.11g or “802.11a/g” as well as the 802.11n standards achievetheir high data transmission rates using Orthogonal Frequency DivisionMultiplexing (OFDM) encoded symbols mapped up to a 64 quadratureamplitude modulation (QAM) multi-carrier constellation. Generallyspeaking, the use of OFDM divides the overall system bandwidth into anumber of frequency sub-bands or channels, with each frequency sub-bandbeing associated with a respective sub-carrier. Data upon eachsub-carrier may modulated with a modulation scheme such as quadratureamplitude modulation, phase shift keying, etc. Thus, each frequencysub-band of the OFDM system may be viewed as an independent transmissionchannel within which to send data, thereby increasing the overallthroughput or transmission rate of the communication system.

Generally, transmitters used in the wireless communication systems thatare compliant with the aforementioned 802.11a/802.11g/802.11n standardsas well as other standards such as the 802.16 IEEE Standard, performmulti-carrier OFDM symbol encoding (which may include error correctionencoding and interleaving), convert the encoded symbols into the timedomain using Inverse Fast Fourier Transform (IFFT) techniques, andperform digital to analog conversion and conventional radio frequency(RF) upconversion on the signals. These transmitters then transmit themodulated and upconverted signals after appropriate power amplificationto one or more receivers, resulting in a relatively high-speed timedomain signal with a large peak-to-average ratio (PAR).

Likewise, the receivers used in the wireless communication systems thatare compliant with the aforementioned 802.11a/802.11g/802.11n and 802.16IEEE standards generally include an RF receiving unit that performs RFdownconversion and filtering of the received signals (which may beperformed in one or more stages), and a baseband processor unit thatprocesses the OFDM encoded symbols bearing the data of interest.Generally, the digital form of each OFDM symbol presented in thefrequency domain is recovered after baseband downconversion,conventional analog to digital conversion and Fast FourierTransformation of the received time domain analog signal. Thereafter,the baseband processor performs frequency domain equalization (FEQ) anddemodulation to recover the transmitted symbols, and these symbols arethen processed in a Viterbi decoder to estimate or determine the mostlikely identity of the transmitted symbol. The recovered and recognizedstream of symbols is then decoded, which may include deinterleaving anderror correction using any of a number of known error correctiontechniques, to produce a set of recovered signals corresponding to theoriginal signals transmitted by the transmitter.

In wireless communication systems, the RF modulated signals generated bythe transmitter may reach a particular receiver via a number ofdifferent propagation paths, the characteristics of which typicallychange over time due to the phenomena of multi-path and fading.Moreover, the characteristics of a propagation channel differ or varybased on the frequency of propagation. To compensate for the timevarying, frequency selective nature of the propagation effects, andgenerally to enhance effective encoding and modulation in a wirelesscommunication system, each receiver of the wireless communication systemmay periodically develop or collect channel state information (CSI) foreach of the frequency channels, such as the channels associated witheach of the OFDM sub-bands discussed above. Generally speaking, CSI isinformation defining or describing one or more characteristics abouteach of the OFDM channels (for example, the gain, the phase and the SNRof each channel). Upon determining the CSI for one or more channels, thereceiver may send this CSI back to the transmitter, which may use theCSI for each channel to precondition the signals transmitted using thatchannel so as to compensate for the varying propagation effects of eachof the channels.

To further increase the number of signals which may be propagated in thecommunication system and/or to compensate for deleterious effectsassociated with the various propagation paths, and to thereby improvetransmission performance, it is known to use multiple transmit andreceive antennas within a wireless transmission system. Such a system iscommonly referred to as a multiple-input, multiple-output (MIMO)wireless transmission system and is specifically provided for within the802.11n IEEE Standard now being adopted. Further, the 802.16 standard,or WiMAX, applies to cell-based systems and supports MIMO techniques.Generally speaking, the use of MIMO technology produces significantincreases in spectral efficiency and link reliability of IEEE 802.11,IEEE 802.16, and other systems, and these benefits generally increase asthe number of transmission and receive antennas within the MIMO systemincreases.

In addition to the frequency channels created by the use of OFDM, a MIMOchannel formed by the various transmit and receive antennas between aparticular transmitter and a particular receiver includes a number ofindependent spatial channels. As is known, a wireless MIMO communicationsystem can provide improved performance (e.g., increased transmissioncapacity) by utilizing the additional dimensionalities created by thesespatial channels for the transmission of additional data. Of course, thespatial channels of a wideband MIMO system may experience differentchannel conditions (e.g., different fading and multi-path effects)across the overall system bandwidth and may therefore achieve differentSNRs at different frequencies (i.e., at the different OFDM frequencysub-bands) of the overall system bandwidth. Consequently, the number ofinformation bits per modulation symbol (i.e., the data rate) that may betransmitted using the different frequency sub-bands of each spatialchannel for a particular level of performance may differ from frequencysub-band to frequency sub-band.

However, instead of using the various different transmission and receiveantennas to form separate spatial channels on which additionalinformation is sent, better transmission and reception properties can beobtained in a MIMO system by using each of the various transmissionantennas of the MIMO system to transmit the same signal while phasing(and amplifying) this signal as it is provided to the varioustransmission antennas to achieve beamforming or beamsteering. Generallyspeaking, beamforming or beamsteering creates a spatial gain patternhaving one or more high gain lobes or beams (as compared to the gainobtained by an omni-directional antenna) in one or more particulardirections, while reducing the gain over that obtained by anomni-directional antenna in other directions. If the gain pattern isconfigured to produce a high gain lobe in the direction of each of thereceiver antennas, the MIMO system can obtain better transmissionreliability between a particular transmitter and a particular receiver,over that obtained by single transmitter-antenna/receiver-antennasystems.

The transmitters and receivers in the wireless communication system mayeach be capable of using a variety of modulation schemes. For example,some modulations schemes may provide a higher bit rate than otherschemes (e.g., 64-QAM vs. 16-QAM). Typically, modulation schemes thatprovide a higher bit rate may be more sensitive to channel impairmentsas compared to modulation schemes with a lower bit rate.

In all communication systems discussed above, as well as in mostwireless communication system, receivers sometimes receive corrupt data,or fail to receive data altogether, because of noise, interference,temporary resource failure, or other reasons. As a result, wirelesscommunication systems typically utilize some sort of noise compensation.Conventional noise compensation methods assume that different transmitand receive antennas experience the same noise powers, which is not truein practice.

SUMMARY

The present disclosure provides methods and apparatus for estimating andcompensating for noise on antennas of a multi-antenna wireless system.

In an embodiment, a method includes receiving a plurality of signals viaa plurality of respective antennas, and estimating a noise powerimbalance across the plurality of antennas by at least estimating aplurality of respective channel gains corresponding to the plurality ofsignals. The method further includes estimating a plurality ofrespective noise powers corresponding to the plurality of antennas usingthe plurality of respective channel gains.

In another embodiment, a method includes receiving multiple signals viamultiple receive antennas of a receiver, where each of the signals isreceived via a respective antenna. The method further includesestimating noise power imbalance corresponding to the receive antennasbased on the multiple signals.

In another embodiment, a method includes receiving multiple signals viaa multiple receive antennas. The method further includes estimatingmultiple noise powers corresponding to the receive antennas based on thereceived signals, where each noise power corresponding to a respectiveantenna.

In another embodiment, an apparatus includes a plurality of noise powerestimators configured to estimate a plurality of respective noise powerscorresponding to respective antennas from among a plurality of antennasby at least generating respective sets of instantaneous noise estimatescorresponding to a plurality of subcarriers of respective signals fromamong the plurality of signals and estimating, based on the sets ofinstantaneous noise estimates, a plurality of respective noise powerscorresponding to the plurality of antennas. The apparatus furtherincludes a plurality of amplifiers configured to scale the plurality ofsignals based on a plurality of scaling factors, the plurality ofscaling factors being generated based on the plurality of noise powers

In another embodiment, an apparatus includes multiple noise powerestimators to estimate respective noise powers corresponding to multiplereceive antennas based on respective signals received via multiplereceive antennas. The apparatus further includes multiple scaling factorgenerators to generate multiple respective scaling factors based on theestimated noise powers. The apparatus further includes multipleamplifiers to scale signals received via multiple antennas based on thegenerated scaling factors.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example wireless communication system.

FIG. 2 is a block diagram of an example data frame.

FIG. 3 is a block diagram of an example multi-antenna receiving devicecapable of estimating and compensating for the noise power on aparticular antenna.

FIG. 4 is a flow diagram illustrating an example method for estimatingand compensating for the noise power on a particular antenna.

FIG. 5 is a flow diagram illustrating another example method forestimating and compensating for the noise power on a particular antenna.

DETAILED DESCRIPTION

Noise power imbalance across antennas of multi-antenna wireless systemsis a common occurrence due to components and circuitry imperfections,and because of differences in background interference affecting variousreceive signal paths. As a result, conventional noise compensationmethods that ignore this noise power imbalance may lead to suboptimalnoise compensation, and more generally, to suboptimal detection anddecoding.

FIG. 1A is a block diagram of an example wireless communication system100 in which a transmitting device 102 transmits information over awireless communication channel 104 to a receiving device 106. Each ofthe devices 102 and 106 may be a base station or a mobile stationequipped with a set of antennas 110-114 and 120-124, respectively.Further, the communication channel 104 includes a K subcarriers C₁, C₂,. . . , C_(K), each associated with a particular frequency at which thedevices 102 and 106 may communicate. The antennas 110-114 and 120-124define multiple spatial streams 130 within the wireless communicationchannel 104 during operation of the devices 102 and 106. In general, thewireless communication system 100 may include any number of devices,each equipped with the same or a different number of antennas such as 1,2, 3, 4, . . . . The wireless communication system 100 may also includeany number of subcarriers. In the embodiment illustrated in FIG. 1, thewireless communication system 100 uses an OFDM technique, and thesubcarriers C₁, C₂, . . . C_(K) are accordingly selected to be mutuallyorthogonal (i.e., to minimize cross-talk between each pair ofsubcarriers). However, the wireless communication system 100 could alsouse any other frequency division multiplexing technique. It will be alsonoted that while the example wireless communication system 100 is a MIMOsystem, at least some of the methods and apparatus for noisecompensation discussed herein may be applied to a system withmultiple-antenna receivers and a single-antenna transmitter.

The transmitting device 102 may transmit OFDM symbols via subcarriersC₁, C₂, , C_(K), to the receiving device 106. Each OFDM symbol mayinclude a number of individual symbols, each transmitted via arespective subcarrier C_(i). A given signal Y_(k,m,n) is a signalreceived by the receiving device 106 on the k-th subcarrier (orfrequency, or tone) via the n-th receive antenna and corresponding tothe m-th OMDF symbol. The received signal may be given by:Y _(k,m,n) =H _(k) S _(k,m) +Z _(k,m,n),  (1)where H_(k), is the channel gain for the k-th tone, S_(k,m) is thetransmitted individual symbol on the k-th tone of the of the m-th OFDMsymbol, and Z_(k,m,n) is noise on the k-th tone of the m-th OMDF symbolfor n-th receive antenna.

FIG. 2 is a block diagram of an example data frame 200 that may be usedin the wireless communication system 100 to transmit signals over awireless communication channel 104. It will be understood, however, thatthe wireless communication system 100 may alternatively use other typesof data frames 200. It will be further understood that although theformat of the data frame 200 is similar to the format of a mixed-modeframe under IEEE 802.11n, the present disclosure is not limited to anyparticular type of a data frame. Moreover, the present disclosure is notlimited to wireless local area networks and contemplates wirelessnetworks in general.

The data frame 200 generally includes different fields that areseparated in time (e.g., the L-STF field 204 a occupies the first 8 μs,the L-STF field 204 b occupies the next 8 μs, and so on). Morespecifically, the data frame 200 includes a data section 206 and apreamble 202 including a number of fields 204, such as training fields(e.g., Legacy Short Training Field (L-STF) 204 a, Legacy Long TrainingField (L-LTF) 204 b) and signal fields (e.g., Legacy Signal Field(L-SIG) 204 c, High Throughput Signal Field (|HT-SIG|) 204 d) that areceiving device 106 may use to estimate the channel. Furthermore, aswill be subsequently described in more detail, fields 204 of thepreamble 202 may also be used to estimate noise power on particularantennas in a multi-antenna wireless system and, consequently, toestimate noise power imbalance across the different antennas.

As an example, the High Throughput Signal (HT-SIG) field 204 d, or theLegacy Long Training Field (L-LTF) 204 b, may be used to estimate andcompensate for the noise power on a particular antenna. The HT-SIG field204, for instance, is generated at the transmitting device 102 from Bbits of information, which includes information about the nature (e.g.,modulation parameters, code rate, payload length, etc.) of the packets.At the transmitting device 102, the B bits are encoded (using e.g., aconvolution encoder) and mapped to Q bits, which are then modulated(e.g., using binary shift keying (BPSK) modulation. Thus, at thereceiving device 106, the HT-SIG field 204 d signal must be demodulatedto recover the Q bits, and the Q bits must be decoded (e.g., using aconvolutional decoder) to recover the original B bits. Similarly, theLFT field 204 b includes known signals (referred to as “pilots”) thatcan be used to derive channel estimates. Consequently, data in theHT-SIG Field 204 d, or in the L-LTF field 204 b may be used to estimatea channel gain Ĥ_(k) for the k-th tone. Ĥ_(k) can then be used toestimate the noise power on a particular antenna and to estimate noisepower imbalance across multiple antennas, as will be subsequentlydescribed.

FIG. 3 is a block diagram of an example multi-antenna receiving device300 capable of estimating and compensating for the noise power on aparticular antenna. The receiving device 300 may be utilized in thewireless communication system 100 as the receiving device 106, forexample. It will be understood, however, that the wireless communicationsystem 100 may alternatively use another receiving device 106.

The receiving device 300 generally includes a number of receive antennas320 for receiving radio signals. The receiving device 300 may furtherinclude RF receiving units (e.g., analog RF front end 330) that performRF downconversion and filtering of the received signals. In order toperform certain processing functions, the receiving devices may convertthe received signal from time domain to frequency domain, using, forexample, Fast Fourier Transform (FFT) units 340. The received signalsmay be converted to frequency domain at various stages of processing.

The receiving device 300 may further include noise power estimators 370that estimate the noise power on different receive antennas 320 andscale generators 380 that generate a scaling factor to compensate forthe noise on the antennas. In order to compensate for the noise on thereceive antennas 320, the receiving device 300 may include amplifiers350 that scale the received signals based on the scale factors generatedby the scale generators 380. Although FIG. 3 illustrates scaling infrequency domain (after the received signals are converted to thefrequency domain by the FFT units 340), scaling may also take place intime domain (before the received signals are converted to the frequencydomain by the FFT units 340). The receiving device 300 may furtherinclude demodulator/decoder units 360 (e.g., including QAM demodulatorsand BPSK decoders) that generally demodulate and decode the receivedsignals into information symbols.

FIG. 4 is a flow diagram illustrating an example method 400 forestimating and compensating for the noise power on a particular antenna.For ease of explanation, FIG. 4 will be described with reference toFIGS. 1-3. It will be understood, however, that the method 400 may beutilized with systems and devices other than those illustrated in FIGS.1-3.

As discussed above, when a receiving device (such as the receivingdevice 106) receives a signal Y_(k,m,n). corresponding to tone k, OFDMsymbol m, received via antenna n (block 402), the receiving device mayuse one or more fields in the received signal (e.g., the L-LTF field 204b) to estimate a channel gain Ĥ_(k) for that tone (block 404). Once thechannel gain Ĥ_(k) is estimated, the receiving device, based on theestimated channel gain Ĥ_(k), may estimate the transmitted signalŜ_(k,m). As an example, the receiving device may estimate Ŝ_(k,m) asfollows:

$\begin{matrix}{{{\hat{S}}_{k,m} = {{sign}\left( {{Re}\left( \frac{Y_{k,n,m}}{{\hat{H}}_{k}} \right)} \right)}},\;{{{sign}(x)} = \left\{ \begin{matrix}1 & {{{if}\mspace{14mu} x} \geq 1} \\{- 1} & {{{if}\mspace{14mu} x} < 1}\end{matrix} \right.}} & (2)\end{matrix}$

Once the transmitted signal for the k-th tone of m-th symbol (Ŝ_(k,m))has been estimated (e.g., using equation 2), the receiving device mayuse this estimation to further estimate the instantaneous noise({circumflex over (Z)}_(k,m,n)) for the k-th tone of m-th symbol on theantenna n in question. In some embodiments, this instantaneous noise canbe estimated as follows:

_(k,m,n) =Y _(k,m,n)−

_(k)

_(k,m)  (3)

The receiving device may perform this process for signals associatedwith other tones and symbols (YES branch in block 410). If there are nomore signals (NO branch in block 410), the receiving device may estimatethe noise power on the antenna (σ_(n) ²) by averaging the noise powersover all tones and all OFDM symbols of the HT-SIG field (block 412), forexample, as follows:

$\begin{matrix}{\sigma_{n}^{2} = {\frac{1}{KM}{\sum\limits_{k,m}\;{{\hat{Z}}_{k,n,m}}^{2}}}} & (4)\end{matrix}$

Once the receiving device estimates the noise power on the antenna, thereceiving device may compensate for the noise by scaling the signals onthat antenna based on estimated power (block 414). For example, thescaled signals {tilde over (y)}_(n) on a given antenna n may berepresented as:

$\begin{matrix}{{{\overset{\sim}{y}}_{n} = \frac{y_{n}}{X\;\sigma_{n}}},} & (5)\end{matrix}$where y_(n) is the signal received via the n-th antenna, and X is anoptional configurable parameter, such as a constant.

As explained in reference to FIG. 3, the signals can be scaled toaccount for noise at various stages in the processing. For instance, thesignals may be scaled in time domain (before the received signals areconverted to the frequency domain by the FFT units 340). The signals mayalso be scaled in frequency domain.

The result of the method 300 described above in reference to FIG. 3 isthat signals received via different antennas are treated differentlywith respect to noise estimation and compensation. More specifically,the receiving device will scale the signals it receives based at leastin part on the antenna via which the receiving device receives thesignal. This leads to an improved detection and decoding of receiveddata.

FIG. 5 is a flow diagram illustrating another example method 500 forestimating and compensating for the noise power on a particular antenna.For ease of explanation, FIG. 5 will be described with reference toFIGS. 1-3. It will be understood, however, that the method 500 may beutilized with systems and devices other than those illustrated in FIGS.1-3.

When a receiving device receives a signal Y_(k,m,n) on a given tone k ofa given OFDM symbol m via a particular antenna n (block 502), thereceiving device may choose one or more fields in the received signal(e.g., the L-LTF field 204 b in the preamble) and demodulate and decodethose fields before decoding the rest of the signal (block 504). Thereceiving device may demodulate and decode those fields using anysuitable techniques. The receiving device may then re-encode andre-modulate the selected fields to form an estimate of the transmittedsignal S _(k,m) (block 506).

Once an estimate of the transmitted signal S _(k,m) is formed, noisepower on the antenna may be estimated and compensated for usingtechniques similar to those discussed in reference to FIG. 3. Inparticular, the receiving device may use this estimation of thetransmitted signal S _(k,m) to estimate the instantaneous noise ( Z_(k,m,n)) for the k-th tone of the m-th OFDM symbol on the antenna n inquestion (block 508).Z _(k,m,n) =Y _(k,m,n)−

_(k) S _(k,m),  (6)where Ĥ_(k) is determined from the information in the fields 204 of thereceived signal, as discussed above.

The receiving device may perform this process for signals associatedwith other tones and symbols (YES branch in block 510). If there are nomore signals (YES branch in block 510), the receiving device mayestimate the noise power on the antenna (σ_(n) ²) by averaging the noisepowers over all tones and all OFDM symbols of the HT-SIG field (block512), for example, as follows:

$\begin{matrix}{\sigma_{n}^{2} = {\frac{1}{KM}{\sum\limits_{k,m}\;{{\overset{\;}{\overset{\_}{Z}}}_{k,n,m}}^{2}}}} & (7)\end{matrix}$

Once the receiving device estimates the noise power on the antenna, thereceiving device may compensate for the noise by scaling the signals onthat antenna based on estimated power (block 514). For example, asdiscussed in reference to FIG. 4, the scaled signals y_(n) on a givenantenna n may be represented as:

$\begin{matrix}{{{\overset{\sim}{y}}_{n} = \frac{y_{n}}{X\;\sigma_{n}}},} & (8)\end{matrix}$where y_(n) is the signal received via the n-th antenna, and X is anoptional configurable parameter, such as a constant.

As explained in reference to FIG. 3, the signals can be scaled toaccount for noise at various stages in the processing. For instance, thesignals may be scaled in time domain (before the received signals areconverted to the frequency domain by the FFT units 340). The signals mayalso be scaled in frequency domain.

The method 500 described above in reference to FIG. 5 is similar to themethod 400 described in reference to FIG. 4 in that both methods treatsignals received via different antennas differently with respect tonoise estimation and compensation. In particular, the receiving devicewill scale the signals it receives by a factor that is based at least inpart on the antenna via which the receiving device receives the signal.Furthermore, the method 500 described in reference to FIG. 5 may beextended to higher modulation with generally better reliability andaccuracy. However, the drawback of method 500 as compared to method 400is that the former may require a more complex implementation and moreprocessing time.

At least some of the various blocks, operations, and techniquesdescribed above may be implemented in hardware, a processor executingfirmware instructions, a processor executing software instructions, orany combination thereof. When implemented in a processor executingfirmware or software instructions, the software or firmware may bestored in any computer readable memory such as on a magnetic disk, anoptical disk, or other storage medium, in a RAM or ROM or flash memory,processor, hard disk drive, optical disk drive, tape drive, etc.Likewise, the software or firmware may be delivered to a user or asystem via any known or desired delivery method including, for example,on a computer readable disk or other transportable computer storagemechanism or via communication media. Communication media typicallyembodies computer readable instructions, data structures, programmodules or other data in a modulated data signal such as a carrier waveor other transport mechanism. The term “modulated data signal” means asignal that has one or more of its characteristics set or changed insuch a manner as to encode information in the signal. By way of example,and not limitation, communication media includes wired media such as awired network or direct-wired connection, and wireless media such asacoustic, radio frequency, infrared and other wireless media. Thus, thesoftware or firmware may be delivered to a user or a system via acommunication channel such as a telephone line, a DSL line, a cabletelevision line, a fiber optics line, a wireless communication channel,the Internet, etc. (which are viewed as being the same as orinterchangeable with providing such software via a transportable storagemedium). The software or firmware may include machine readableinstructions that are capable of causing one or more processors toperform various acts.

Although the forgoing text sets forth a detailed description of numerousdifferent embodiments, it should be understood that the scope of thepatent is defined by the words of the claims set forth at the end ofthis patent. For example, one or more steps of methods described abovemay be performed in a different order (or concurrently) and stillachieve desirable results. The detailed description is to be construedas exemplary only and does not describe every possible embodimentbecause describing every possible embodiment would be impractical, ifnot impossible. Numerous alternative embodiments could be implemented,using either current technology or technology developed after the filingdate of this disclosure, which would still fall within the scope of theclaims.

What is claimed is:
 1. A method comprising: receiving a plurality ofsignals via a plurality of respective antennas; and estimating a noisepower imbalance across the plurality of antennas by at least estimating,for each signal, a respective set of channel gains corresponding to aplurality of sub-carriers, and estimating a plurality of respectivenoise powers corresponding to the plurality of antennas, includingestimating, for each signal, the corresponding noise power using therespective set of channel gains.
 2. The method of claim 1, whereinestimating the plurality of respective noise powers is based onrespective portions of the plurality of signals corresponding to a fieldin a preamble of a data unit.
 3. The method of claim 1, whereinestimating the noise power imbalance further comprises determining anestimate of a transmitted signal as transmitted by a transmitter;wherein estimating the plurality of respective noise powers furthercomprises using the estimate of the transmitted signal.
 4. The method ofclaim 3, wherein determining the estimate of the transmitted signal astransmitted by a transmitter comprises: decoding and demodulating aportion of a field in a preamble of a data unit to provide a decoded anddemodulated portion of the data unit, wherein the data unit correspondsto the plurality of signals; and re-encoding and re-modulating thedecoded and demodulated portion of the data unit.
 5. The method of claim1, further comprising: scaling the plurality of signals based on theestimated noise power imbalance.
 6. An apparatus, comprising: aplurality of noise power estimators configured to estimate a pluralityof noise powers corresponding to respective antennas from among aplurality of antennas based on a plurality of signals received via theplurality of antennas, wherein each noise power estimator from among theplurality of noise power estimators is configured to estimate arespective set of channel gains corresponding to a plurality ofsubcarriers in the respective signal, and estimate the respective noisepower using the respective set of channel gains; and a plurality ofamplifiers configured to scale the plurality of signals based on aplurality of scaling factors, the plurality of scaling factors beinggenerated based on the plurality of noise powers.
 7. The apparatus ofclaim 6, wherein each noise power estimator from among the plurality ofnoise power estimators is configured to estimate the respective noisepower based on a portion of the respective signal corresponding to afield in a preamble of a data unit.
 8. The apparatus of claim 6, whereineach noise power estimator from among the plurality of noise powerestimators is configured to determine an estimate of a transmittedsignal as transmitted by a transmitter, and estimate the respectivenoise power using the estimate of the transmitted signal.
 9. Theapparatus of claim 8, further comprising: a plurality ofdemodulator/decoders, each demodulator/decoders from among the pluralityof demodulator/decoders being configured to decode and demodulate aportion of a signal corresponding to a respective antenna to provide adecoded and demodulated portion of the signal; wherein each noise powerestimator is configured to re-encode and re-modulate the respectivedecoded and demodulated portion of the signal to generate the estimateof the transmitted signal as transmitted by the transmitter.
 10. Amethod comprising: receiving a plurality of signals via a plurality ofrespective antennas; and estimating a noise power imbalance across theplurality of antennas by at least generating respective sets ofinstantaneous noise estimates corresponding to a plurality ofsubcarriers of respective signals from among the plurality of signals,and estimating, based on the sets of instantaneous noise estimates, aplurality of respective noise powers corresponding to the plurality ofantennas.
 11. The method of claim 10, wherein estimating the respectivenoise powers comprises: estimating respective noise powers by, at least,determining a respective average of instantaneous noise estimates inrespective sets of instantaneous noise estimates.
 12. The method ofclaim 10, further comprising: scaling the plurality of signals based onthe plurality of noise powers.
 13. The method of claim 12, whereinscaling the plurality of signals comprises: generating a plurality ofrespective scaling factors corresponding to the plurality of antennasbased on the plurality of respective noise powers; and scaling theplurality of signals with the plurality of scaling factors.
 14. Anapparatus, comprising: a plurality of noise power estimators configuredto estimate a plurality of respective noise powers corresponding torespective antennas from among a plurality of antennas by at leastgenerating respective sets of instantaneous noise estimatescorresponding to a plurality of subcarriers of respective signals fromamong the plurality of signals, and estimating, based on the sets ofinstantaneous noise estimates, a plurality of respective noise powerscorresponding to the plurality of antennas; and a plurality ofamplifiers configured to scale the plurality of signals based on aplurality of scaling factors, the plurality of scaling factors beinggenerated based on the plurality of noise powers.
 15. The apparatus ofclaim 14, wherein each noise power estimator from among the plurality ofnoise power estimators is configured to estimate the respective noisepower by, at least, determining a respective average of instantaneousnoise estimates in the respective set of instantaneous noise estimates.16. The apparatus of claim 14, wherein each noise power estimator fromamong the plurality of noise power estimators is configured to generatethe respective set of instantaneous noise estimates based on a portionof a respective signal corresponding to a field in a preamble of a dataunit.
 17. The apparatus of claim 14, further comprising: a plurality ofdemodulator/decoders, each demodulator/decoder from among the pluralityof demodulator/decoders being configured to decode and demodulate aportion of the signal corresponding to the respective antenna to providea decoded and demodulated portion of the signal; wherein each noisepower estimator is configured to: re-encode and re-modulate therespective decoded and demodulated portion of the signal to generate arespective estimate of the transmitted signal as transmitted by thetransmitter, and estimate the respective set of instantaneous noiseestimates based on the respective estimate of the transmitted signal astransmitted by the transmitter.
 18. The apparatus of claim 14, furthercomprising: a plurality of scale generators configured to generate theplurality of scaling factors based on the plurality of noise powers.